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Journal ArticleDOI

Identification of continuous-time systems

G.P. Rao, +1 more
- Vol. 153, Iss: 2, pp 185-220
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TLDR
Continuous-time model-based system identification as mentioned in this paper is a well-established field in the field of control systems and is concerned with the determination of particular models for systems that are intended for a certain purpose such as control.
Abstract
System identification is a well-established field. It is concerned with the determination of particular models for systems that are intended for a certain purpose such as control. Although dynamical systems encountered in the physical world are native to the continuous-time domain, system identification has been based largely on discrete-time models for a long time in the past, ignoring certain merits of the native continuous-time models. Continuous-time-model-based system identification techniques were initiated in the middle of the last century, but were overshadowed by the overwhelming developments in discrete-time methods for some time. This was due mainly to the 'go completely digital' trend that was spurred by parallel developments in digital computers. The field of identification has now matured and several of the methods are now incorporated in the continuous time system identification (CONTSID) toolbox for use with Matlab. The paper presents a perspective of these techniques in a unified framework.

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Citations
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Journal ArticleDOI

Subspace-based multivariable system identification from frequency response data

TL;DR: Two noniterative subspace-based algorithms which identify linear, time-invariant MIMO (multi-input/multioutput) systems from frequency response data are presented.
BookDOI

Identification of Continuous-time Models from Sampled Data

TL;DR: Identification of Continuous-time Models from Sampled Data brings together contributions from well-known experts who present an up-to-date view of this active area of research and describe recent methods and software tools developed in this field.
Book

Errors-in-Variables Methods in System Identification

TL;DR: The paper gives a survey of errors-in-variables methods in system identification, and a number of approaches for parameter estimation of errors invariables models are presented.
Book

Identification of Dynamic Systems: An Introduction with Applications

TL;DR: This book treats the determination of dynamic models based on measurements taken at the process, known as system identification or process identification, and covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation and subspace methods.
Journal ArticleDOI

Continuous-time model identification from sampled data: Implementation issues and performance evaluation

TL;DR: In this article, the authors deal with equation error methods that fit continuous-time transfer function models to discrete-time data recently included in the CONTSID (CONtinuous-Time System IDentification) Matlab toolbox.
References
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Book

System Identification: Theory for the User

Lennart Ljung
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Book

System identification

Book

Nonlinear Problems in Random Theory

TL;DR: A series of lectures on the role of nonlinear processes in physics, mathematics, electrical engineering, physiology, and communication theory was given in this article, where the last few of these were devoted to the application of my ideas to problems in the statistical mechanics of gases.
Journal ArticleDOI

System identification-A survey

TL;DR: The survey explains the least squares method and several of its variants which may solve the problem of correlated residuals, viz. repeated and generalized least squares, maximum likelihood method, instrumental variable method, tally principle.